54 assistant-professor-computer-science-data Postdoctoral positions at Oak Ridge National Laboratory
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Requisition Id 14997 Overview: We are seeking a postdoctoral fellow to help develop world-class capabilities related to manufacturing science and technology associated with the Oak Ridge National
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Requisition Id 14907 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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related field completed within the last 5 years. Research background in S/TEM or SPM. Strong proficiency in mechanical design and computer aided design (CAD) and 3D modeling. Preferred Qualifications
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the Environmental Risk and Energy Analysis Group. The candidate will work with a multi-disciplinary group of experts in economics, engineering, computer sciences, and physical sciences on the economics and policy
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equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in Computational Science/Engineering or a related field
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instrumentation and apply these in advancing nGI for material science research through novel instrumentation and computational methods. Then you will be applying nGI in addressing critical scientific questions in
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computer engineering, computer science, physics, chemistry, materials science, chemical engineering, or a related field. Demonstrated ability to communicate research results in peer-reviewed publications and
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to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science
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challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
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data production at next-generation computational facilities enables scientific knowledge discovery but presents a challenge to move, store, and process the data. To maximize their science return